Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Classification of Google Play Store Application Reviews Using Machine Learning

Version 1 : Received: 25 July 2020 / Approved: 26 July 2020 / Online: 26 July 2020 (17:11:09 CEST)

How to cite: Karim, A.; Azhari, A.; Alruily, M.; Aldabbas, H.; Brahim Belhaouri, S.; Adil Qureshi, A. Classification of Google Play Store Application Reviews Using Machine Learning. Preprints 2020, 2020070646 (doi: 10.20944/preprints202007.0646.v1). Karim, A.; Azhari, A.; Alruily, M.; Aldabbas, H.; Brahim Belhaouri, S.; Adil Qureshi, A. Classification of Google Play Store Application Reviews Using Machine Learning. Preprints 2020, 2020070646 (doi: 10.20944/preprints202007.0646.v1).

Abstract

Google play store allow the user to download a mobile application (app) and user get inspired by the rating and reviews of the mobile app. A recent study analyzes that user preferences, user opinion for improvement, user sentiment about particular feature and detail with descriptions of experiences are very useful for an application developer. However, many application reviews are very large and difficult to process manually. Star rating is given of the whole application and the developer cannot analyze the single feature. In this research, we have scrapped 282,231 user reviews through different data scraping techniques. We have applied the text classification on these user reviews. We have applied different algorithms and find the precision, accuracy, F1 score and recall. In evaluated results, we have to also find the best algorithm.

Subject Areas

Machine Learning; Natural Language Processing; Text Mining; Semantic Analysis; Scraping; Google Play Store; Rating

Comments (0)

We encourage comments and feedback from a broad range of readers. See criteria for comments and our diversity statement.

Leave a public comment
Send a private comment to the author(s)
Views 0
Downloads 0
Comments 0
Metrics 0


×
Alerts
Notify me about updates to this article or when a peer-reviewed version is published.
We use cookies on our website to ensure you get the best experience.
Read more about our cookies here.